Volume: 1

Issue: 5

August - September 2015

` 10/-

Bimonthly, Chennai

A Bi-monthly Magazine of Indian Wind Turbine Manufacturers Association Volume: 1

Chairman Mr. Madhusudan Khemka Managing Director Regen Powertech Pvt. Ltd., Chennai

Issue: 5

August - September 2015

Contents

Page No.

Message from Ms. Varsha Joshi, IAS, Joint Secretary, MNRE 3

Vice Chairman Mr. Chintan Shah

With contribution from the Danish Wind Industry Association - by

President & Head, (SBD) Suzlon Energy Limited, Pune

Shruti Shukla (Director, Policy and Projects, GWEC)

Honorary Secretary Mr. Devansh Jain Director, Inox Wind Limited, Noida

Executive Members Mr. Ramesh Kymal Chairman & Managing Director Gamesa Renewable Pvt. Ltd., Chennai

Mr. Sarvesh Kumar Deputy Managing Director RRB Energy Ltd., New Delhi

Mr. V.K. Krishnan Executive Director Leitner Shriram Mfg. Ltd., Chennai

Mr. Ajay Mehra Director, Wind World India Limited, Mumbai

Secretary General Mr. D.V. Giri, IWTMA, Chennai

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By 2020 Denmark to Meet its 50% Wind Energy Target

Wind Energy under Full Sail?

5

Clinton Davis, VP Renewable Solutions, Enterprise Software, ABB, Sacramento, California, USA

Forecasting Project in Tamil Nadu - Interview with IWPA Chairman Prof. Dr. K. Kasthurirangaian

9

Scheduling & Forecasting in Rajasthan - An IWTMA Initiatve

12

Om Taneja, Associate Director, IWTMA, New Delhi

Wind Energy Forecasting and Scheduling in India

14

Balawant Joshi, Managing Director, Idam Infrastructure Advisory Pvt. Ltd. Mumbai

Framework for Scheduling and Forecasting of Renewable Energy

18

Dr. Balaraman K and Chandra Shekhar Reddy Atla M/s Power Research & Development Consultants Pvt Ltd., Bangalore

Wind/Solar Power Forecasting and the Way Forward

26

Siddhartha Priyadarshi and Vishal Pandya, REConnect Energy Solutions Private Limited

Scheduling and Despatch in Indian Power System

30

Balaji V., Deputy General Manager, SRLDC, POSOCO, Bangalore

Know Your Wind Energy State - Tamil Nadu - A Snapshot

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Compiled by Mr. Nitin Raikar, Suzlon Energy Limited, Mumbai

Snippets on Wind Power

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Photo Feature: Tamil Nadu Global Investors Meet, SAD Meeting

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Know Your Member - WINDAR Renewable Energy

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Associate Director and Editor Dr. Rishi Muni Dwivedi, IWTMA, Chennai

Views expressed in the magazine are those of the authors and do not necessarily reflect those of the Association, Editor, Publisher or Author's Organization.

Indian Wind Turbine Manufacturers Association 4th Floor, Samson Tower, 403 L, Pantheon Road, Egmore Chennai - 600 008. Tel : 044 43015773 Fax : 044 4301 6132 Email : [email protected] [email protected] Website : www.indianwindpower.com (For Internal Circulation only)

From the Desk of the Chairman - IWTMA

Dear Readers, Greetings from IWTMA! The Ministry of New and Renewable Energy has announced the 2nd Edition of RE-Invest in February 2016. The inaugural session of RE-Invest 2015 inaugurated by the Hon’ble Prime Minister of India, made the industry think from MW to GW with a laudable target of 100 GW of Solar, 60 GW of Wind and 15 GW from other RE sources. The endorsement of enthusiasm is still active in the minds of the manufacturing community and the investment community and to a large extent the financial institutions as well. However, State issues of Policies and Regulations on a concurrent subject like power is not allowing capacity addition to take place as the industry expected. As against a target of 4 GW in 2015-16, the industry lingers around 2.2 GW to 2.3 GW annually. To address this issue, IWTMA along with CII-GBC is conducting Regional Workshops in prominent wind states with all the stakeholders as they are the prime movers in this number crunching game. The Regional Workshops will cover the states of Andhra Pradesh, Telangana, Maharashtra, Gujarat, Rajasthan and Madhya Pradesh and culminate with a National Conclave in Delhi. Various agencies have estimated the wind resource potential of the country and we now have final official Wind Resource Assessment document from National Institute of Wind Energy (NIWE) with a potential of 302 GW. This was formally launched by the Hon’ble Minister for Coal, Power and Renewable Energy, Shri. Piyush Goyal, recently in Delhi. While the Green Corridor Development Programme to help connectivity and evacuation is progressing, Government is seized of the exciting opportunities in interstate transaction and not limit to the host state alone. The industry expects waiver of CTU charges and rationalizing STU charges. Wind Power over the years has carried the label of infirm power which is a limitation to higher penetration and a source worry for the State Load Management Centre. Forecasting and Scheduling and its techniques have been practiced in many countries. NIWE has taken up a programme along with MNRE, TANGEDCO and IWPA for forecasting and scheduling of wind power in Tamil Nadu. Similarly, IWTMA has taken up a programme in Rajasthan to be replicated in other wind states. In this issue of ‘INDIAN WIND POWER’, we have a special theme on Forecasting and Scheduling with articles contributed by renowned persons in this field. COP21 on Climate Change and Global Warming is due in November ’15 in Paris. Many countries are endorsing energy security through RE sources and a few countries have given up coal and oil stocks. IWTMA dedicates itself for energy contribution to control pollution and carbon foot print. We do hope that the thinkers and planners of our country share the same thoughts in our movement towards “Clean Green Power Forever”. Wishing our Readers a Happy Dussehra and Colourful Diwali to brighten our hopes and future of our nation. With warm regards,

Madhusudan Khemka Chairman

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By 2020 Denmark to Meet its 50% Wind Energy Target With contribution from the Danish Wind Industry Association by Shruti Shukla (Director, Policy and Projects, GWEC) expected to happen more frequently in the future with more capacity to be built and integrated. Denmark used this surplus electricity in other parts of the energy system especially in the transport and heating sectors. The Danish district heating system covers over 60% of all buildings and provides excellent opportunities for using electricity at times when wind energy production is high and prices are low.

Denmark is a unique case study for wind power generation and integration both onshore and offshore. The government’s ‘strategic intent’ is to carry this renewables based transition of its energy system to its logical end i.e. zero dependence on oil and gas. By 2020 Denmark plans for wind energy to occupy a 50% share of its electricity generation as part of its plans to phase out fossil fuels by 2050. The share of wind power in the Danish electricity consumption has increased steadily during the last three years from 30% in 2012, to 33% in 2013. In 2014, wind turbines provided 39.1% of Danish electricity. This share is expected to grow further this year. Today globally, Denmark has the highest consumption of wind energy on a per capita basis. In 2014, 860 kW of wind energy was installed per 1,000 Danish citizens. In comparison, this number was 250 kW for the other EU-28 countries. Denmark has been a historical leader in the development of wind power technology. It has focused on developing a robust, transnational and flexible integrated energy system, which is capable of handling large volumes of variable renewable energy generation. Denmark’s energy system provides secure and stable electricity supply to its consumers, while increasingly integrating wind energy into the grid. From time to time there are days when wind turbines produce more than a 100% of Denmark’s electricity needs. This is

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Decades of successfully integrating wind energy into the power system have given Denmark the know-how and confidence to set a deadline for moving beyond fossil fuel use. According to Energinet.dk, the transmission system operator supplying Denmark with electricity and natural gas, Denmark is in the process of transitioning from an energy system where generation is adapted to consumption to one where consumption is adapted to generation. Implementation of this long-term energy plan requires an increased scalability in energy production, consumption and trading. Grid operators and energy companies are specialised in forecasting the production and demand for renewable energy in Denmark and neighbouring countries (Germany, Norway and Sweden) as part of the Northern European power market. Further efforts are on-going to interlink to the Dutch and the UK power markets. Energinet.dk is working closely with the transmission system operator TenneT, supplying the Dutch and German markets, to build a 700 MW and 320 km submarine cable linking the Danish and Dutch electricity system. Energinet. dk is also working together with National Grid, the transmission system operator in England to assess the possibilities of laying a 600 km cable to the UK. By 2035 wind is likely to meet 75% of the demand for heat and power, with about half of that coming from offshore wind capacity. Denmark’s experience with wind power can provide valuable lessons for Indian grid operators and power producers towards meeting the government’s stated target of 175GW of renewables based generation by 2022.

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August - September 2015

Wind Energy under Full Sail? Despite Challenges, Forecasting and Scheduling Technology is helping Wind to become an increasingly Important and Reliable Source of Energy Clinton Davis, VP, Renewable Solutions, Enterprise Software, ABB, Sacramento, California, USA There has never been a more challenging time in the power industry than today, but also perhaps never a time so full of opportunity. One the one hand, modern electricity transmission and distribution networks are undergoing dramatic changes. They have to cope with more distributed and renewable energy resources, more data from smart power equipment and meters and more regulatory pressure to run efficiently. Adding to the complicated changes at play, the typical distribution network is changing from one that connects producers and consumers in a one-way power flow to one that carries flow in both directions in a complex, dynamic way.

On the other hand, each day seems to present power producers with new and better ways to leverage the growing resource of renewable energy, particularly wind – as installations over the last several years have demonstrated. The ABB Energy Advisors Reference Case models, which provide 25-year forecasts of power markets demonstrate this fact in key markets such as the US and Germany, generally seen as bellwethers for the renewable power industry (see Figures 1 & 2). Thanks to recent developments in energy resource forecasting and scheduling technology, wind has an increasing capacity for greater integration onto the power grid, enhancing wind’s reliability as a power source.

Figure 1

Source: Internal ABB - ABB Energy Advisors Reference Case model; North American Reference Case

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Figure 2

Source: Internal ABB - ABB Energy Advisors Reference Case model; German Reference Case

Improvements in Wind Forecasting Another area where technology is helping power producers to leverage wind is the area of forecasting. Weather-based business forecasting has become a serious business. Advancements in forecasting technology are having a tremendous impact for energy executives calculating future renewable investments. While the nature of forecasts means that outcomes are sometimes far from what was forecasted, no prudent investor or utility will get involved in a renewables project without some pretty serious consideration of how things might look in the future. There’s a rough continuum from higher to lower certainty in making predictions. For the forecasting done to determine the viability of prospective wind or solar farms, we can look backward and do a solid job of projecting forward to predict potential availability of sun and wind at a given site. Current forecasting systems also do a good job of helping asset managers and maintenance crews schedule service more efficiently. We see less of the run-to-failure or fixedinterval approaches to decide when to dispatch crews. Instead, asset managers are increasingly assessing actual asset health

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information to forecast probable mean time between failures. That enables service at a time when it’s really needed, but before the turbine blades stop spinning. Short-term forecasts of renewable energy availability continue to improve due to more sophisticated sensors, monitoring and data processing capabilities, and highly granular fundamental climate predictions. Both renewable energy providers and utilities need to know how much power can be produced and available in the coming hours in order to optimize generation and ensure a sufficient supply of power. As the timeframe moves out from hours to decades, we enter the realm of big picture, long-term forecasting that is far more challenging. It’s tough to answer questions like “What is the value of this wind farm over the next 25 years?” with a great deal of certainty. Which isn’t to say that this kind of forecasting has no value. It does a tremendous job of providing scenarios related to technical and commercial factors. What happens if the portfolio of available renewables goes up 20 percent in 10 years? Forecasting helps answer some really interesting questions about what should be done to best profit from renewables investment.

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Advanced Technology for Enhanced Forecasts ABB helps make this a reality with its advanced solutions like Nostradamus and PROMOD. Nostradamus is used for mainly short-term forecasting of renewable resources such as wind and solar, and regional demand. It uses a neural network enabling users to track forecasts with actual values as well as update new information as it becomes available. The neural network algorithm learns the pattern of load or price changes from numerous weather variables as well as day of week, time of year and holidays by learning from historical data. Other input data includes historical load, weather, price, customer /account, transmission, congestion, and generation data. During day to day operations, the system can augment what it has learned with new information (called “dynamic weighting adjustment”). Furthermore, Nostradamus can plot actual vs. forecast over time to give the finest detail needed to clearly isolate specific points in time where the new model is not measuring up (see Figure 3). This allows users to make necessary changes quickly. PROMOD takes as input the forecasts and optimizes system operation (generation and transmission) to ensure system

demand is met at least cost while conforming to transmission and generation operational, technical and commercial constraints. A generator and portfolio modeling system, PROMOD provides nodal Locational Marginal Price (LMP) forecasting and transmission analysis by producing algorithms that align with the decision focus of management. Among its nodal features are renewable energy curtailment to simulate the effects of intermittent energy schedules from wind on transmission congestion, and forecast the amount of energy that would be curtailed considering the opportunity costs from production tax credits. And, a key zonal feature is power market analysis for quantifying the operating risks associated with each facility and developing a detailed forecast of market prices and system operation under various conditions.

Summary Forecasting will never be perfect, but it can be very accurate. Even when it isn’t, it is helpful for planning around the volatility and uncertainty of policy, weather, prices and a host of other issues. Considering the critical need to predict commercial, technical and operational aspects of renewable energy generation, forecasting is certainly something to which investors, planners, and operators need to devote considerable attention.

Figure 3

Source: Internal ABB

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Forecasting Project in Tamil Nadu Interview with IWPA Chairman Prof. Dr. K. Kasthurirangaian Introduction: IWPA has taken the initiative in Tamil Nadu for setting up of a State-wide Forecasting mechanism for 7500 MW to enable optimal evacuation of wind energy. To understand this mechanism, Editor, “Indian Wind Power” magazine and Associate Director, IWTMA (Indian Wind Turbine Manufacturers Association) Dr. Rishi Muni Dwivedi had an interview with IWPA Chairman Prof. Dr. K Kasthurirangaian. We thank him for very clear and specific answers about the project.

1. What is the future of wind energy within the overall energy mix? Dr. K.K.: Wind energy is the only source of energy which does not require water at all. Wind energy installations in India are growing at 27% CAGR (Compound Annual Growth Rate). Currently, India is the fourth largest country in the world in terms of wind energy installations. Given the decisions of various State Electricity Regulatory Commissions about the RPO fixation and its enforcement, we believe it will take the growth of wind energy to 20% of the total energy required by 2022. We are hopeful that India will achieve the target of 60 GW, set by the Government.

2. Please tell why your Association has taken up this Forecasting Project? Dr. K.K.: Ideally, this infrastructure should have been facilitated by the Government. Two to three billion units of wind power was being lost each year in 2013 and 2014 because of back down of Wind Mills since there is no mechanism to predict the wind generation and the investors are affected financially. Industries depending on captive power from wind mills were affected the most. Utility lost the opportunity to buy cheap and clean power available in the State. The consumers were also affected.

Forecasting at Substation Level As you are aware, the high wind season lasts only for five months from May to September every year. If evacuation does not take place during these five months, we will not only lose God’s gift of free and clean energy but investors will also loose heavily.

3. Why is Forecasting so essential in evacuating wind energy? Dr. K.K.: Forecasting is essential for scheduling wind energy primarily for the following two reasons: a.

Energy should be consumed as soon as it is generated. Presently, we do not have a storage mechanism for such large quantum of energy.

Hence the Association with the support of its Wind Generator Members decided to come forward and sponsor the setting up of the facilities as an “industry sponsored project” utilizing the capability of NIWE.

b.

Wind energy is not only seasonal but is variable and intermittent. We have to provide a visibility to Grid operator as to how much of wind energy is likely to be generated.

We are thankful that the MNRE, State Government and NIWE had readily accepted the offer and thus the project is taking shape.

Wind energy is termed as “infirm power” since there is wide variation from one day to the next and also the intraday variation can be high.

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Thankfully these days we have the technology to assess with a reasonable degree of accuracy of how much wind energy is likely to be generated in the next 15 minutes, next one hour, next day, one week ahead, etc. The information regarding the likely generation of wind power, will help the SLDC to give visibility of the likely quantum of generation of wind energy and helps to schedule the power thus facilitating evacuation optimally.

4. Why was NIWE chosen as the Forecasting Service Provider? Dr. K.K.: This is an interesting story. We have made this offer of installing the forecasting infrastructure to Tamil Nadu SLDC almost two years back. We had even mentioned that the infrastructure once installed would be the property of the SLDC. However, the SLDC was hesitant to accept this offer from the generators. In February 2015, the Government organized the REINVEST at New Delhi. An ambitious target of 175 GW of renewable energy, which includes 60 GW of wind energy was announced by the Government. The very next month sometime in May 2015, Government soon realised that in order to increase capacity the evacuation problems primarily in Tamil Nadu had to be resolved. As you know, Tamil Nadu accounts for 40% of the wind energy installations in the country. MNRE came to the conclusion that having a reliable forecasting mechanism is the only answer to ensure further growth of the wind industry. Therefore, MNRE in consultation with the SLDC had sanctioned expeditiously a Pilot Forecasting Project in Tamil Nadu at Ayyanaruthu Wind Pooling substation. NIWE was given the responsibility of implementing the project. It was a coincidence that just a year back four of the scientists at NIWE were trained in Spain in the Forecasting software. When we learnt of this development, with the support of most of our Wind Generator Members we offered to sponsor the entire project thus enlarging the scope of the Pilot Project. This proposal was readily accepted by MNRE, NIWE and TANGEDCO. That is how NIWE became an important Forecaster in this Project.

5. What is the MNRE’s role in this project? Dr. K.K.: MNRE has been a pillar of support for RE development. Without MNRE’s intervention and push this project would not have taken off in such a short notice. The role played by MNRE is crucial not only in the sanctioning of the project but also getting all the constituents together and bringing coordination amongst them. This project is complex and numerous hurdles are coming when we are taking this project forward. Thankfully we are in the last leg and we hope to complete the project by the end of August 2015. Therefore, this wind season,

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the wind generators had benefitted partially but next year we will see the full benefits of installing this Forecasting mechanism.

6. Is the State Utility using the forecast data given by NIWE/IWPA? Dr. K.K.: Presently, we are giving forecast based on the partial installations. However, this has a fairly good accuracy. It is through this process that on August 11, 2015, 84.359 million units was evacuated which is the highest evacuation till date. The system needs to be finetuned for better accuracy. Since this is the first project of its kind, there is obviously a few teething troubles and some learning involved. It is like learning to ride a bicycle. We may falter here and there before mastering the art of riding the bicycle. Same analogy holds good for the Forecasting exercise.

7. Tell us briefly how this system works? Dr. K.K.: To give a forecast we need the following three inputs: a.

Past historical data for two years. This will give the generation pattern in the immediate past. This is a crucial input to the software algorithm for generating the forecast. This data is taken from the past hand written records maintained at the individual Wind Pooling Substations.

b. Real time generation of wind energy. This is provided by the setting up of self-consuming energy meters at the Wind Pooling Substations. The meters will furnish real time data i.e. how much wind energy is being generated right now. This real time data is relayed to the servers located at NIWE / SLDC automatically as configured. Generally, when generation is taken across a larger geographic area, the accuracy is better & works out deeper. c.

Meteorological Data. This involves getting satellite data of the prevailing weather condition (present and predicted) where all the wind mills are located. Therefore, the GPS coordinates i.e. Latitude and Longitude of each and every wind mill and substation is needed for the purpose as well as hub height & Power curve of WEG. All the three types of data are synthesized in the Forecasting software and the Forecast output is generated. It is through this process that we are able to predict with a reasonable level of accuracy the likely wind generation. It may be mentioned that the accuracy level depends upon the quality of input. If reliable input is given

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then the accuracy goes up otherwise there could be deviations. Nevertheless with the passage of time the Forecasting model has to be trained to provide better accuracy over a period of continuous real time data the accuracy will improve. The deviations can be contained to a single digit.

8. How these data are analysed? Dr. K.K.: The data analysis is done at NIWE. Firstly, the historical data given to NIWE is digitized in a specific form and fed into the software model developed by NIWE in collaboration with Vortex Factoria de Calculs, S.L. a Spanish company which is specialised in Forecasting. NIWE has created an automated system to pick up and process the real-time generation data. This processed input is continuously fed into the forecast model.

9. What are the difficulties in adapting the data? Dr. K.K.: Generally, it is the quality pertaining to the onetime input of historical data. These data are manually recorded since SCADA systems are not available in all the Wind Pooling Sub-stations. Since the historical data is recorded manually it is time consuming to collect data at Site & to digitize and verify the accuracy of the data entry. This has caused a delay in implementing the project. At a few substations, which were newly installed, there are no SCADA data. The specification of the meters as approved by TANGEDCO/ TANTRANSCO had meter reading with two decimals. NIWE wanted more accuracy and insisted on the meter reading to reflect to one millionth of a unit. The meters had to be

recalibrated to six decimal units and this further delayed the process. All these meters were custom built exclusively for the project. There were also connectivity issues due to network. For example, a few SS located in remote areas when they face power outages, there is a break in the transmission of data from the individual SS to NIWE. Such incidents affected the flow of real-time data. Real-time generation data is one of the key inputs in updating the forecast data. Due to sudden changes in atmospheric conditions, the pattern may suddenly change, which the software is not able to at times quickly adapt to these sudden changes. These are some of the difficulties we faced when NIWE was analyzing the data, but all have been overcome.

10. What is the current deviation and how can this deviation be minimised and improve the accuracy? Dr. K.K.: Presently on an average the deviation is contained within 10%. With more training and accuracy of inputs, we expect the deviation could be brought down.

11. How will this project fit within the overall framework of the REMC (Renewable Energy Management Centre) proposed by PGCIL (Power Grid Corporation of India Ltd.)? Dr. K.K.: We have been given a draft of the REMC framework and a clear picture is yet to emerge. PGCIL may be installing REMC in TN in 2015-16. We have requested PGCIL officials to expedite installation and promise them all support from IWPA. These details will emerge in the coming months.

Wind Atlas Released by NIWE NIWE has released its wind resources assessment findings in the form of a wind atlas launched by the Minister of State (Independent Charge) Power, Coal and New & Renewable Energy, Piyush Goyal, on 2nd September 2105. India’s installable wind energy potential has been estimated to be 302 GW with towers of a height of 100 metres. This will help in development of hybrid solar and wind systems which would help stabilize the grid and better utilize the transmission network. Earlier, India’s wind energy potential was measured to be at around 100 GW with a tower height of 80 metres.

August - September 2015

Indian Wind Power

NATIONAL INSTITUTE OF WIND ENERGY Formerly Centre for Wind Energy Technology (C-WET)

Chennai NIWE is organising 18th National Training Course on “Wind Energy Technology” from 26th to 30th October 2015 at Chennai. For details please visit the NIWE website www.niwe.res.in or write to [email protected].

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Scheduling & Forecasting in Rajasthan An IWTMA Initiatve Om Taneja, Associate Director, IWTMA, New Delhi IWTMA has taken an initiative of coordinating Scheduling & Forecasting for the state of Rajasthan. The state has the total installed capacity of approx 3300 MW. The major players are Suzlon, Wind World, Inox, Regen Powertech & Gamesa. Most of the projects are SCADA enabled and connected to State Transmission Units (STU) with DISCOM.

•

regulation for submission to SLDC. •

•

A study of available systems at Pooling sub stations is under progress and once the study is over, one of the coordinating agencies (aggregator) will be selected to take over, who will be responsible for:

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SLDC,

RDPPC,

Sub

Stations,

To arrange actual generation report from Developers/

•

Analysis of Actual & forecasted Data and subsequent effects

•

To prepare Daily, Weekly & Monthly Reports covering Analysis, Shortcomings, issues of curtailment by SLDC, Actual Vs Forecasted Deviation etc.

We believe that the State of Rajasthan will be totally connected by accuracy on forecasting and scheduling by the year end. Rajasthan Rajya Vidyut Prasaran Nigam Limited has written to MNRE appreciating the efforts of IWTMA for the initiative taken in collection and consolidation of forecasting data from various generators.

SLDC SCADA in IEC 104 protocol Aggregator’s analyzing System GPRS Modem with IEC 104 Protocol

OEM Routers

Substation 1

Substation 2

1Mbps

GPRS Modem with IEC 104 Protocol

1Mbps

IWTMA 1Mbps

This exercise will be beneficial for all the stakeholders, like developers, generators, SLDC Rajasthan, Power Distribution companies of Rajasthan, Rajasthan discom power procurement centre etc.

with

Investors /DISCOM

IWTMA is consolidating a forecast of above 2900 MW on day ahead basis and forwarding to SLDC before 10:30 AM daily. This schedule is expected to cover above 3200 MW by end of the year.

The proposed scheme (tentative) for the exercise is as sketched below.

Co-ordination

Developers / Investors or any other designated agency.

Presently SLDC is not equipped for analysis of deviation between scheduled power and actual injection. There is no Data integration system in between Pooling substations and SLDC for getting the details of Power injection at any time. SLDC is getting data on phone/email and manually maintain a log book, which is not very reliable as the data is received at different timings, hence not comparable. Availability of actual data of Injected Power is possible only after 30 days from the MRI record.

Presently IWTMA is playing a role as a single co-ordinating agency for compiling all Forecast data as received from various generators and forwarding to SLDC. This exercise is static in nature and IWTMA is working to make the exercise dynamic form of S&F, so that the prevailing Regulations can be adhered to and the exercise is useful for the state.

Compilation of schedule data included all Revisions, as per

Inox

Internet Service Provider cloud

GPRS Modem with IEC 104 Protocol

Substation 3

Windworld

GPRS Modem with IEC 104 Protocol

Substation “N”

Gamesa

Indian Wind Power

Regen

Suzlon

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www.windworldindia.com

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Wind World (India) Ltd. Wind World Towers, Plot No. A-9, Veera Industrial Estate, Veera Desai Rd., Andheri (W), Mumbai 400 053, India. Tel: +91 22 6692 4848 | Email: [email protected]

Wind Energy Forecasting and Scheduling in India Balawant Joshi, Managing Director, Idam Infrastructure Advisory Pvt. Ltd., Mumbai

Introduction India has the fourth highest wind installed capacity in the world. As on 30.06.2015, the total installed capacity for wind energy in India was 23,763 MW. With such large scale wind power deployment, and with even more aggressive target for harnessing the wind energy in the near future, wind industry is going to play a significant role in the operation of electricity markets and power systems. In the past, on several occasions, System Operators in India have been forced to curtail wind energy generation though wind enjoys ‘Must Run’ status owing to its intermittent nature. This has resulted in loss of generation and revenue for wind projects impacting the project viability. The practice of forecasting wind power generation and scheduling the same is envisaged as a potential solution to tackle the issues posed by the intermittency. This is also expected to increase the acceptability of intermittent generating source like wind among the system operators and allow better management of the Grid.

Different approaches to forecasting: Wind forecasting is generally based on the required forecasting horizon; which is broadly categorised based on duration-long term (day ahead/ seasonal) and short term (hour ahead) forecast. The basic approaches for forecasting are enlisted below: •

Physical Method (Numerical Based): A Numerical Weather Prediction (NWP) model is the commonly used method for forecasting of weather elements represented by equations of physics through the use of numerical methods.

•

Statistical Method: In this method, relationship between wind speed prediction and measured power output from the wind farm is derived to predict the wind power.

•

Hybrid Method: It is a combination of above mentioned forecasting methods with the proper tools.

Different approaches to scheduling: The key approaches to

Basics of Forecasting and Scheduling

scheduling adopted globally are mentioned below:

Need for forecasting and scheduling: Given the ambitious target set by Government of India, of adding 60 GW wind power by 2022, there is an urgent need for streamlining the mechanism of forecasting and scheduling wind energy for proper grid integration.

•

Forecasting: The prediction of wind energy available for generation in the future is called forecasting. Forecasting is done with the help of forecasting tools which combines meteorological data (wind speed, temperature, etc.) and turbine level data (type of turbine, installed capacity, swept area, hub height, etc.) into an algorithm and a forecast is generated. Scheduling: The process of generating schedules (in MW or MWh) based on the forecast created on day ahead or intra-day basis for a certain time block (fifteen minutes) for the proper dispatch of energy. Apart from wind energy forecasts, schedules also take into consideration issues such as grid availability, machine maintenance etc.

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Decentralized Scheduling: In this method each wind farm needs to forecast and schedule its generation. This type of mechanism is preferred for wind generators who wish to participate in open access or day ahead or intraday markets.

•

Centralized Scheduling: In case of centralized scheduling, the forecasting is done by a single entity (the grid operator in most cases) for all wind projects in the control area. Generally, the wind energy generation forecasts prepared for larger control area are consistent and have higher accuracy levels.

•

Integrated Scheduling: It is a combination of the above mentioned scheduling techniques wherein centralized schedules are created for all wind farms in a cluster and decentralized schedule are created for captive and open access wind farms.

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Regulatory Framework for Scheduling in India

•

Error (%) = 100 * (Actual Generation - Scheduled Generation) / (Available Capacity)

The concept of forecasting and scheduling of wind generators and commercial settlement thereof was first introduced in Indian context by CERC through Indian Electricity Grid Code

Where, Available Capacity (AvC) is the cumulative capacity rating of the wind turbines and solar inverters that are capable of generating power in a given time-block. AvC will be equal to the installed capacity unless one or more turbines are under maintenance or shutdown.

(IEGC), 2010. The RRF or the ‘Renewable Regulatory Fund’ mechanism was envisaged to be implemented from January 1, 2011. However, owing to several implementation issues, the mechanism was never made operational. In order to formulate an implementable framework, CERC on 31.03.2015, issued draft Amendments to (i) the Central Electricity Regulatory Commission (IEGC) Regulations, (ii) the Central Electricity Regulatory Commission (Deviation Settlement Mechanism and Related Matters) Regulations and (iii) the Central Electricity Regulatory Commission (Terms and Conditions for recognition and issuance of Renewable Energy Certificate for RE Generation) Regulations. Based on the comments and suggestions received from various stakeholders, CERC has published the 3rd

Error Calculation: The formula for error calculation is :

•

Imbalance Handling: The tolerance band being proposed is +/-15% for wind and solar generators. The settlement in case of over or under injection would be as follows: Absolute Error in S the 15 minute time No. block

Deviation charges payable to Regional DSM pool

1.

Within +/- 15%

No commercial implication

2.

>15% but 25% but 35%

30% of PPA rate

amendment to IEGC. It is called Central Electricity Regulatory Commission (IEGC) (Third Amendment) Regulations, 2015

and related matters.

Brief Snapshot of the Recent Amended Regulations The CERC has amended the IEGC to accommodate mechanism for Forecasting, Scheduling and Imbalance Handling for Renewable Energy (RE) generating stations based on wind and solar energy. The salient features of the framework are mentioned below: •

Applicability: Wind and Solar generators which are regional entities.

•

Forecasting responsibility: Forecasting shall be done by wind and solar generators which are regional entities as well as by RLDC. The forecast by the concerned RLDC shall be responsible for ensuring secure grid operation while the forecast by wind/solar generators shall be generator centric.

•

Scheduling Responsibility: The responsibility of providing generation schedule lies with wind and solar generators. They have the option of accepting the concerned RLDC’s forecast for preparing its schedule or they can prepare schedule based on their own forecast.

•

Revision of schedules: There may be a maximum of 16 revisions for each fixed one and half hour time slot starting from 00:00 hours during the day.

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Indian Wind Power

In case of multiple PPAs, the weighted average of the PPA rates shall be taken as the PPA Rate.

International Experience In German power sector, currently more than 75 GW of RE capacities are subject to forecasting. The German power transmission system is subdivided into four areas, each run by an independent TSO. Forecasting is done for wind generators located in the control area by the respective TSO. The forecast horizon is typically up to three days and temporal resolution of the forecast is of fifteen minutes to one hour. The Wind Power Management System (WPMS) which is developed by ISET is used by the four TSOs for forecasting of wind power. The accuracy of the predictions has significantly improved over the last year and is roughly above 95%. In order to improve wind power forecasts intense research and development efforts are already on track. In Spain, Red Eléctrica de España, S.A. (REE), the Spanish TSO, is dedicated to the transmission of electricity and the operation of electricity systems of Spain. REE, started a Control Centre of Renewable Energies (CECRE) in 2006, to monitor and control renewable energy generation in Spain and to cope up with the issue of intermittency of these sources. REE was one of the first TSOs in the world to have a power forecasting system integrated with other tools in real-time operations. Hourly forecasts for

15

the next 48 hours are computed by region or the node at the transmission system. REE uses forecasts which are computed using single or combination of forecast models provided by multiple forecast providers. REE constantly performs comparison of forecasting errors to track the forecasts with the least error and better performance. It is observed that combined forecast is better since the mean absolute error is the lowest for all time horizons. TSO in Spain was able to reduce the errors with the help of forecasts from multiple forecast providers.

Developments in India: Gujarat Owing to high wind energy potential, significant wind power projects have been commissioned in the state of Gujarat. Hence, in order to contain wind generation variability, several initiatives have been undertaken in the state to improve wind energy forecasts and thereby assist System Operators in maintaining the stability of the grid. Analysis of the existing conditions reveals that significant variations exist not only in physical infrastructure but also in institutional mechanisms within the state. A few wind farm developers in Gujarat have initiated forecasting wind generation and providing day-ahead schedules to SLDC. The state has also installed RTUs at all 220 kV and above substations for remote data transfer to SLDCs. Real time renewable energy (Solar & wind) generation data is integrated with existing system and posted on the website of Gujarat SLDC. It is important that the detailed assessment of Gujarat experience of wind forecasting & scheduling is undertaken and gaps in processes, systems and institutional structure are

identified for successful implementation of the forecasting and scheduling framework in across India.

Key Issues The key issues which need to be addressed for successful implementation of a forecasting and scheduling mechanism would include: ²² The roles of implementing institutions such as SLDC, RLDC, NLDC and RPC should be clearly defined. ²² It is important to analyse the preparedness of all wind rich states viz. Gujarat, Rajasthan, Karnataka, Tamil Nadu, Maharashtra, etc., for implementation of such mechanisms at the State level. ²² Improvement of infrastructure facilities and formulation of suitable procedures, protocols and capacity building/ training of staff at the implementing institutions (SLDC, RLDC, NLDC, RPC, SNA) should be undertaken.

Conclusion The level of RE penetration (in terms of energy generated) in India is presently around 5 to 6 percent. While the capability of generators to forecast generation and to provide timely schedules are key requirements, it is equally important that other institutions involved, whether central level or state level are adequately prepared. Apart from wind/solar generators, the implementing institutions such as SLDC, RLDC, NLDC and RPC need to be geared up with adequate infrastructure and trained manpower.

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Framework for Scheduling and Forecasting of Renewable Energy Dr. Balaraman K

Chandra Shekhar Reddy Atla

M/s Power Research & Development Consultants Pvt Ltd., Bangalore

1. Introduction Renewable energy capacity (in particular wind and solar) in India has increased exponentially in the past few years. This increase in variable generation has led to issues in integrating it to the power system in particular in system operation. The system operator has to ensure reliability & security of the system and hence there is a need to forecast and schedule these variable renewable energy generations. Scheduling and forecasting of the wind generation is presently being discussed and debated in India citing its importance and role in system operation and security. Considering the relevance of the subject, a roadmap suggesting possible forecasting and scheduling strategies for India and implementation frameworks for the same are evolved. The roadmap covers: •

Scheduling process

•

Forecasting services

•

Error computation

•

Data management

2. Scheduling Process As per present regulations in India, decentralized scheduling is adopted which mean that each of the wind farm with the connected capacity of 10 MW and above at interface point to the grid submits its schedule to the system operator. It is observed that most countries prefer centralized or cluster-based scheduling with the concept of virtual power plants. The practices followed are:

18

•

Centralized scheduling for committed wind farms through PPA: An independent body or system operator carries out the scheduling and forecasting on behalf of all the wind farms.

•

Individual wind farms who participate in the market: The wind farms participate in the open

electricity markets through bidding process and settlement takes place according to the market rules. Here, scheduling & forecasting is the responsibility of the wind farm owners. There are advantages and disadvantages of both the approaches. For power system operation and security, the centralized mechanism is preferred. The summary of various methods is described below.

2.1 Decentralized Scheduling Mechanism In this mechanism, each wind farm forecasts and schedules its generation. The mechanism is preferred for wind farms who wish to participate in open access or day ahead or intraday markets. As the schedule is available from individual wind farms, the transmission line congestion would be known in advance and appropriate actions can be initiated. However, each wind farm follows its own forecast mechanism and there is no consistent approach. With many wind farms, the huge number of schedules received by the system operator may create difficulties in managing the schedules. As each wind farm has to maintain the scheduling and forecasting system, there is no optimization of costs as well as forecasting system. The accuracy of the forecasting is also less as compared with cluster or system level due to less geographic area of wind farm considered for forecasting.

2.2 Centralized Scheduling Mechanism The centralized scheduling mechanism would result in reduction in forecast error due to aggregation taking advantage of geographic diversity and smoothing of forecasting errors. This mechanism can provide consistent wind power forecasting and methodology for all wind projects in the region, which will likely lead to more consistent results. With its sheer magnitude and resources, it would promote technological advances and research for better forecasting system.

Indian Wind Power

August - September 2015

The grid operator shall have access to wind generation data (and perhaps on-site weather data from all the wind plants) that can be used to improve the performance of centralized scheduling & forecasting system. Whereas in decentralized forecast method by wind farms, the system operator may not have access to wind generation data because of proprietary or confidentiality reasons. A centralized scheduling system may be able to utilize economies of scale, reducing the cost of forecasting as compared to decentralized forecasting systems. However, the centralized forecasting system may have inconsistency as it can be based on single forecasting methodology and provider. This can be overcome by creating structure with the competitive model and the fees paid to the forecast provider dependent on the accuracy of the forecast. The system operator receives the wind power forecast for entire state or area as one entity and hence the system operator can see one overall wind power forecast value. Under this mechanism system operator does not perform the wind power forecast for individual wind farms. Further, it would be difficult to anticipate transmission line congestion if only the aggregate forecast is available for entire region. It is observed that both the mechanisms have their own merits and would be useful for different purposes. Considering the Indian context where the future wind farms can trade power through any route, adopting any one particular mechanism may not serve the purpose of system operation and security. Hence it is proposed to have an integrated scheduling mechanism where the wind farms entering into PPAs with the utilities would be covered under centralized forecasting system whereas the wind farms that are into captive use or participate in the bilateral market (either through power exchange or third party sales) could follow the decentralized mechanism.

2.3 Integrated Scheduling Mechanism In this approach, it is proposed for centralized wind power forecast for each of the identified clusters and individual, wind farm/solar farm forecast for the investors who wish to participate in the energy market. This provides high accuracy as compared with decentralized forecast due to diversity of wind farms over the area/cluster. These clusters can be described as virtual power plant for all practical purposes. Under this mechanism, system operator can see the wind power forecast values for each cluster. These schedules can be integrated with the EMS (Energy Management System) and would enable the system operator to handle transmission line congestion.

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Indian Wind Power

With economics of scale, it would be possible to reduce the cost of forecasting and at the same time promote forecast by ensemble methods (i.e., systems that make use of a variety of methodologies or forecast providers) that use five or more forecasting services to improve the forecast accuracy. In this mechanism, all the wind farms in the clusters would be considered (irrespective of date of commissioning) for the forecasting. In view of range of wind turbines commissioned in the last decade, wind farms would be categorized into three levels. First, there are plants that had no turbine and nodal-level generation or meteorological data; these can be labeled as Level 1 wind plants. These include plants that were not included in the data gathering effort and are not metered. Second are the ones in which only total power output is known at the interconnection point (Level 2). These tend to be plants that were not included in the data gathering effort but are metered. These are plants that are technically incapable of providing real-time data and/or are small in installed power. For example, turbines built prior to 2005 tend to be technically incapable of providing real time data via the architected data collection system and plants less than 10 MW were not pursued unless bundled together with other larger plants. Lastly, there are plants which are SCADA connected, that can provide turbine-level and nodal-level details (Level 3). Most of the wind farms commissioned post 2006 have the capability to provide the real time SCADA data (with minor modification in the wind farms wherever it is needed) and would constitute around 70% of the wind generation in country. The level 3 wind farms would form the base for the forecasting and for the remaining wind farms, upscaling methods would be used to arrive at their generation. Thus in the proposed approach, the system operator would have complete information of the wind generation in the cluster and can plan their activity by considering them as virtual power plant for their operation. Individual wind farm who are contracted by captive use and third party sales, would forecast their generation and submit their schedule to the System Operator (SO). The gaming by these wind farms would also be prevented in this approach as the intended generation in the cluster would be known through the centralized forecasting system, and if the schedule deviates beyond certain percentage, then the system operator can initiate appropriate action to correct their schedule.

19

The number of clusters are unique for a particular state. This can be decided upon by performing certain data analysis in depth. However, based on the research, the clusters are formed as shown in Table 1 for integrated scheduling and forecasting for high wind penetration states. Table 1. Clusters for Integrated Scheduling & Forecasting State

Area/zone wise Wind generation passes

Tamil Nadu

Muppandal, Udumalpete, Theni, Thirunelveli

Karnataka

Chitradurga, Chikkodi, Gadag

Rajasthan

Udaipur, Jaisalmer, Jodhpur

Gujarat

Kutch, Saurashtra

Maharashtra

Sangli, Ahmednagar, Satara

2.4 Framework for Scheduling Process To sustain the integrated scheduling mechanism, it is necessary to have a Scheduling Coordinator (SC) for each state. The scheduling coordinator will manage all the wind farm clusters in that state. In the proposed approach, the system operator has been designated as the scheduling coordinator for managing the functions and based on the experience gained; a separate agency under the system operator can be assigned this task. The funds for forecasting services and deviations can be provided from fund collected as “Scheduling, Forecasting and Deviation (SFD) Fund” from all wind and solar developer/ investor on per MW basis and this shall be managed by the scheduling coordinator of the state. At present in decentralized forecast mechanism, the cost of forecasting services varies from Rs.1250 to 1750 per MW per month for the wind farms. With the economics of scale with wind clusters coupled with competition, these charges may come down to less than Rs.1000 per MW per month. On top of this, wind farms would need to pay deviation charges if schedules go beyond the limit specified in the regulations. In the proposed approach, it is recommended to invite bids from qualified forecast providers for each cluster (they would be called as service providers (SPs)). It could be ensured that at least two service providers be appointed in every state to be able to compare their services. In the transition period, the service providers can

22

be paid the fee for their services which shall be scaled based on the forecast accuracy. The transition period may be 2 to 3 years. The fees for these services can be funded through SFD. In the transition period, SLDC/designated agency may have to be compensated from both SFD fund and centrally operated fund (green energy fund) for balance of actual deviation cost. After transition period, the deviation from the forecast would be accounted by SLDC/ designated agency through SFD fund only. After transition period, it is recommended that for each cluster, competitive bids can be invited for services of forecasting, scheduling and deviation. The bids would be similar to uplift charges based on per MW basis for each cluster which would be a virtual power plant. The successful bidder may be paid from the SFD fund for all the services offered. The Deviation Settlement Mechanism (DSM) would be applicable for each of the clusters and could be same as applicable to utilities. Considering the present deviation settlement mechanism, the overall charges per year for the wind farm would range from Rs.2 Lakhs/MW to around Rs.5 Lakhs/MW. In the proposed mechanism, the wind farms can be categorized into 2 categories as presented below. Category 1: Wind farms with valid PPAs •

With DISCOMs within the state

•

With DISCOMs of other states (for inter-state trading of wind power)

Category 2: Wind farms not having PPAs •

Market based wind power sales through open access

•

Captives

2.4.1 Category 1: Wind Farms with Valid PPAs The wind farm owners are free to enter into PPA with same state DISCOMs or other state DISCOMs. In this category, wind farm owners or developers would pay fee per MW towards SFD fund. The UI charges, deviation settlement will be accounted by SLDC through SFD fund. For wind PPAs with other states DISCOMs, the additional transmission charges need to be accounted. The clusters will be formed in a particular state and the SC will be responsible for scheduling, forecasting and settlements of deviations for these clusters. As explained earlier, these services are procured from the service providers based on the fees derived from the bids. The

Indian Wind Power

August - September 2015

monopoly over forecasting services shall not be entertained as this will lead to inconsistency and inaccuracy. Hence, it is advisable to always procure forecast services from more than one service providers. This will also lead to enhanced forecasting results as different forecast providers use different techniques/methodologies. For wind farms with PPAs with inter-state DISCOM, the schedule can be given by the SC as a percentage of installed capacity in that cluster for the inter-state sales. For example, if the total installed capacity of cluster is say 1000 MW and scheduled generation given by SC for this cluster is 600 MW. If one wind farm having installed capacity of 100 MW in this cluster has PPA with inter-state DISCOM, then the schedule of this 100 MW wind farm for the inter-state DISCOM during this period is 60 MW.

2.4.2 Category 2: Wind Farms not having PPAs The wind farms under this category could forecast their generation schedule by themselves as per the regulations. Any deviations from the committed power shall be settled according to the deviation settlement mechanism as followed by the utilities. If actual generation is higher than the schedule given by wind farm owner, then for the extra generation, the wind farm would be paid at Average Pooled Purchase Cost (APPC) of the respective DISCOM/state, and the wind farm could be allowed to sell corresponding RECs (Renewable Energy Certificates) in the market. If actual generation is lower than the schedule given by wind farm owner, the wind farm could pay the DISCOM an Average Pooled Supply Cost (APSC) for the shortfall in generation and buy RECs from the market. In both the cases, the wind farm shall make good the REC. For these wind generators the fee payable would be a certain percentage of the fee (SFD Fund) as they are accounted separately for a deviation settlement. System coordinator provides the schedules for clusters for both category-1 and category-2 wind farms for system operation purpose. These cluster schedules are used for the system operation but deviation settlements would be accounted separately. However, there could be a provision for penalty if the schedule of the category-2 wind generators deviate more than a certain percentage of the cluster forecast given by SC. In order to better understand the perspective of deviation settlement in case of category-2 wind farms, a sample

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Indian Wind Power

calculation is made. The deviation in a time block is taken as the difference of actual total injection and total scheduled generation. Thus, a positive deviation implies over-injection. The deviation charges for additional injection of the power would be paid at APPC while for deviation for shortfall in injection shall be paid for at APSC. The detailed computations simulations carried out reveal that the total charges earned by the developer/investor is lower in the proposed APPC & APSC approach as compared to the present approach of deviation settlement mechanism as stated in section 2.4.1. This implies that the earnings from the deviations are considerably reduced thereby encouraging the developers/investors to make a more accurate forecast.

3. Forecasting Services Presently, forecasting in India is carried out by companies such as 3-Tier, Garrad Hassan, AWS Truepower etc. Most of their services are based on the models created based on European/USA context and is applied in India. There is a need to create a comprehensive and competitive mechanism for forecasting services in India. Forecasts highly rely on high quality of meteorological and other data (both historical and real time data) made available in a timely manner to the forecast providers for use within their models. The data includes the following real time data, meteorological data and static data as shown in Table 2. Table 2. Data Required for Wind Power Forecast Turbine data Real time data

Static data

Meteorological Tower Data at sensor heights

Turbine generation

Latitude & Longitude

Wind speed

Nacelle wind speed

Hub Height (m)

Wind direction

Wind direction

Turbine Model

Temperature

Turbine availability status (or equivalent on wind farm level)

Manufacturer’s Power curve

Pressure

Air density

23

It is proposed that the regulation shall make it mandatory for providing the real time data by all the wind farm owners depending on the levels (level 1 to 3 as defined in section 2.3) described earlier.

6. Way Forward As a way forward, the following points are recommended: •

Changes in state/central Grid Code to incorporate the scheduling and forecasting processes by the system operator/designated agency or through service providers.

•

The scheduling, forecasting and deviation settlement for third party sales and captive generation by the respective wind farm owners.

•

CERC could introduce changes in IEGC (Indian Electricity Grid Code) to mandate data sharing by wind farms.

•

Regulations concerning the deviation mechanism, if it is separate from the conventional schemes.

•

Creation of SFD fund and institutional mechanism. Considering the present deviation settlement mechanism, the overall charges per year for the wind farm would range from Rs.2 Lakhs/MW to around Rs.5 Lakhs/MW.

•

Guidelines for selecting the forecast service providers by state regulators.

4. Error Computation As per present regulations, the error computation is with respect to schedule power. As wind generation varies from zero to maximum, the error distribution is very wide with respect to schedule. Worldwide practice is to compute error with respect to installed capacity. Error with respect to installed capacity provides the operator/stakeholders to understand the deviations better provided the wind farm owners share the turbine availability information for the scheduling intervals. Hence it is recommended to use the error deviations with reference to installed capacity for comparing the forecasting services. This shall be used for payment for forecasting services to provide level playing field.

5. Data Management and Data Repository System operator or scheduling coordinator needs to maintain databases for renewable energy sources in addition to existing conventional data in Data Exchange Centre (DEC). The data management is critical for better forecasting and future operation. Hence it is recommended that the data sharing by the wind farms be made mandatory as part of the regulation. The regulation shall provide the manner in which the data to be shared along with data interval mechanism on par with other conventional power plants.

Acknowledgment This study has been conducted by Power Research & Development Consultants Pvt. Ltd. with support from Shakti Sustainable Energy Foundation in the year 2014. We thank the support of Mr. Deepak Gupta and Ms. Disha Agarwal from Shakti Sustainable Energy Foundation for their continuous support during the project.

Snippets on Wind Power

 MERC Reduces MSEDCL Distribution Tariff

24

The Maharashtra Regulatory Commission (MERC) in a notification dated June 27, 2015, has calculated the Distribution Tariff for Maharashtra State Electricity Distribution Company Limited (MSEDCL), which will be effective from 1st June 2015 onwards. The commission in the present order has surprisingly reduced the tariffs for industrial and commercial consumers. The details of the tariff for commercial and industrial consumer are given in the table below. MSEDCL Existing Tariff Energy Charges

MSEDCL Revised Tariff Energy Charges

% Change

HT I (A) - Industry (Express Feeder)

8.41

7.21

-14.27%

HT I (B) - Industry (Non Express Feeder)

7.60

6.71

-11.71%

HT I (C) - Seasonal Industry

9.35

7.8

-16.58%

(A) Express Feeder

12.54

11.15

-11.08%

(B) Non-Express Feeder

11.8

10.62

-10.00%

Category HT I - Industry in Rs/kWh

HT II - Commercial in Rs/kWh

Indian Wind Power

August - September 2015

Wind/Solar Power Forecasting and the Way Forward Siddhartha Priyadarshi

Introduction

Vishal Pandya

REConnect Energy Solutions Private Limited

Wind and solar energy are two variables by nature which change very drastically even within 24 hours. The variation in the generation is majorly caused by variation in the atmospheric parameters, which vary enormously over shorter periods of time causing spontaneous changes in energy generation output. The uncertainty and variability of the wind energy generation has been a cause of operational concern for the power system operators, as they have to maintain smoother grid operations by managing the injection and load with granularity of every 15 minute. With the increasing capacity of grid connected wind power, it has become equally important to maintain its effective integration with the grid, by using technology and mechanisms it can helps to reduce the negative impact of its infirm nature and assist the grid operators in easily accommodating wind power. The graphs below explain the typical characteristics of variation in wind energy generation during the course of a day, in both the high wind season and low wind seasons.

High Wind Season:

Low Wind Season:

(Ref: Forum of Regulator’s Study as published recently)

Solar

Brief about Forecasting & Scheduling

India is blessed with 300+ days of clear sunny weather during

Wind forecasting operations are represented in the diagram below:

the day, with huge solar power potential remaining to be tapped. In case of solar power, where generation happens over the day time only, the variations are not as high as wind. The generation trend during the day ideally follows a bell shaped curve, unless it is affected by cloudy or rainy conditions. Hence, it is important to capture variations in solar power especially when we are aiming to reach 100GW of solar power capacity over next 7 years.

26

Indian Wind Power

August - September 2015

Wind F/C - Model Tested and implemented; - MAPE of ~15% at State Level tested for GJ

Demand F/C Solar Power F/C - Model tested - Model ready for Karnataka - 50 MW - MAPE under achieved operations ~2.9%*

Our experience with different forecasting algorithms is depicted in the diagram below:

The calculations above are based on the earlier method of error calculation, and not with respect to installed capacity as per the new regulation for inter-state. Much higher accuracy can be achieved, with telemetry (real time and historical) data, if available.

Wind & Solar Forecasting & Scheduling Regulations: Drivers of RE Grid Integration To overcome the difficulties related with managing the infirm wind and solar power, the Central Electricity Regulatory Commission introduced the provisions for wind/solar power forecasting under the Indian Electricity Grid Code in May 2010. The mechanism was promoted as the Renewable Regulatory Fund (RRF) mechanism. The mechanism was originally intended to be implemented by January 2011, which got four extensions (Jan’12, Jul’12, Feb’13, July’13) before it could get even started. The mechanism finally got implemented from 15th July, 2013 and subsequently got caught under the litigations as the Wind Associations challenged the decision of CERC to implement such regulations for wind power plants connected under the intra-state networks. Finally, the commercial settlement related with the mechanism finally went to temporary suspension mode in Feb’14.

The mechanism also attracted lot of resistance from various stakeholders due to the reasons represented in the block diagram below. The mechanism covered only wind/solar capacity commissioned after May, 2010 hence, leaving significant part of existing capacity beyond the regulatory coverage.

States could not make much use of the partial forecast data for improving their grid operations. Hence, the demand for bringing the remaining existing capacity started arising.

Issues faced with the RRF Mechanism

Neither the States or the Wind Generators were happy as the ex-post nature of settlement due to UI linked penalty structure created huge financial risks for States as well as Wind Generators.

Hence, the demand for a simpler but a broader framework for forecasting and scheduling started arising from States as well as Wind/Solar Generators.

Central Electricity Regulatory 2015 Commission (Deviation Settlement Mechanism and related matters) (Second Amendment) Regulations,

Central Electricity Regulatory Commission (Indian Electricity Grid Code) (Third Amendment) Regulations, 2015

•

Scheduling of wind and solar generators which are regional entities, has been made mandatory for aggregated capacity of 50 MW and above.

•

UI settlement account has been removed, and replaced by the Deviation Settlement Mechanism (DSM).

•

Maximum number of revisions increased from 8 to 16 revisions on a daily basis. Need for mandatory disclosure of real time SCADA / telemetry data and

• plant availability information to SLDC / RLDC.

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Indian Wind Power

• • • •

Forecast error methodology has been changed, to bring plant availability into perspective, by calculating deviation with respect to plant availability in each time block. Penalties on deviation beyond +/- 15%. Delinking the commercial scheme with the prevailing frequency of the grid, so as to avoid uncertainties in calculation of settlement and the possibility of gaming. Net settlement of RECs shall be done monthly bythe nodal agency, thus protecting the interests of the generators from the uncertainties of the REC market.

27

CERC Forecasting and Scheduling Regulations 2015 The CERC on 05th April 2015 proposed new framework for the Forecasting, Scheduling and imbalance handling of Wind and Solar Energy generating projects at inter-state level, and finalized the same through notification on 7th August, 2015, to make major amendments to the Deviation Settlement (DSM) Regulation 2014 and the IEGC Regulation 2010. The highlights of the same are given below:

Error Calculation Methodology: The error calculation methodology used earlier and the proposed one are compared below: RRF Regulation 2013

New Inter State Regulation 2015

Error (%) =

Error (%) =

100 X (Scheduled Generation – Actual Generation)

100 X (Scheduled Generation – Actual Generation)

Scheduled Generation

(AvC)

Remarks: This formula yielded a larger forecast error, especially

Remarks: Available capacity for generation (AvC). It becomes

in the low wind season when the forecast is low and the

obligatory for the generator to report availability. Thus, it puts

deviations are higher. Even with a very good forecast, due to

more liability on the OEM/O&M of the project to ensure

very low generation, the deviations maybe insignificant, but the

maximum availability, and on the forecaster to ensure that the

errors could still be beyond +/- 30%, putting financial liability

deviation is low, by also factoring plant availability whenever

on the generators.

required.

The penalty mechanism as per the new regulation is as follows: Deviation within +/15%

No penalty

Full payment

Deviation from 15% to 25%

Penalty of 10% on

Fixed Rate

Deviation from 25% to 35%

Penalty of 20% on

Fixed Rate

Deviation greater than 35%

Penalty of 30% on

Fixed Rate

•

For single PPA agreements, the fixed rate shall be the PPA rate between the generator and buyer, and in case of multiple PPAs, the weighted average shall be taken.

•

For Open Access transactions for RE, where consumer is not claiming RPO, or in case of captive power, the fixed rate shall be the APPC rate at the national level.

Way Forward: Intra-state Regulations The existing wind capacity of 23.7 GW1, most of which comes under the control area of the state, whereas in case of solar, approximately 200 MW odd capacity out of 4 GW2 comes under the control area of RLDCs. With the central government thrust on large additions year-on-year, in future, large inter-state projects will come under purview of the new inter-state forecasting regulation. However, the regulation for accommodating the capacity connected with the state control area can be expected to be announced soon as the CERC in its closing remarks of the final regulation has expressed the desire for the same. We are expecting the Intra-state regulation to come soon, along with the implication of the commercial settlement. With the implementation of the Inter-state regulation becoming applicable from 1st November 2015, and possibly, the soon to come Intrastate regulation, it is a huge task at hand for all stakeholders, especially for those generators for whom forecasting and scheduling will be something new to oblige to, when the new regulations are implemented. It also calls for more efficient approach in terms of huge data management schema, automation of operations, forecasting techniques and error handling & response. 1 2

28

As per MNRE data on 30.06.2015 As per MNRE data on 30.06.2015

Indian Wind Power

August - September 2015

Scheduling and Despatch in Indian Power System Balaji V., Deputy General Manager, SRLDC, POSOCO, Bangalore

Abstract Scheduling of electric power generators and drawee entities is the first and foremost step in enforcement of accountability and grid discipline. The mechanism has paved way for creation of power market in India and implementation of various mile stones such as Availability Based Tariff (ABT), Open Access, Congestion Management Ancillary Services, etc. It has greatly improved the frequency profile, grid security, stability and has made grid disturbances a thing of past. In this brief article, an attempt is made to explain how Scheduling is carried out, how it has changed the way the power system operated in India,

how it would help large scale integration of renewable energy sources and the way forward.

Introduction Scheduling is a process where a generator declares the amount of power it can inject to grid in a time block and the beneficiary / drawee entity (State) requisition the amount of power it intends to draw from its supply sources. Scheduling is hailed as one of the four pillars of a power market (Making competition work – Sally Hunt), but it is truly the fundamental pre-requisite for any Power System.

ELECTRICITY MARKET SCHEDULING & DISPATCH

IMBALANCE Settlement Mechanism

ANCILLARY SERVICES

CONGESTION MANAGEMENT

Figure 1 Four Pillars of Market Design - “Making Competition Work in Electricity”, Sally Hunt

Till the mid of 2002, accounting of the Generation

PERCENTAGE OF TIME FREQUENCY IN NORMAL BAND (49.0-50.5 Hz) 100.00

and Drawl used to be based on a single reading

90.00

of energy meters taken at the end of the month.

80.00

This sample of time block was absurdly huge

70.00

operation. A spate of grid disturbances, (black outs and brown outs) compelled the Players

% OF TIME

and festered grid indiscipline and suboptimal

60.00 50.00 40.00

in the Grid to ultimately concede to adopt

30.00

Scheduling

was

20.00

introduced in India in a phased manner from

10.00

July 2002(WR), Dec 2002 (NR), Jan’2002(SR),

0.00

mechanism.

Scheduling

Apr’2003 (ER) and Nov ‘2003 (NER) as a part of the new Imbalance settlement mechanism called ABT (Availability Based Tariff).

30

1995-96

POST ABT / ULDC

PRE ABT / ULDC

1996-97

1997-98

NorthernRegion

1998-99

1999-00

2000-01 YEAR

Western Region

2001-02

2002-03

Southern Region

2003-04

2004-05

2005-06

Eastern Region

Figure 2 Improvement in Frequency in terms Plot of % time soon after Scheduling started

Indian Wind Power

August - September 2015

generation in the grid. The maximum value of Deviation rate is designed in such a way that as the frequency falls, the costlier generation is increased, thus ensuring the Load-Generation balance in the Grid.

Scheduling Process

Figure 3 Max, Min & Average Frequency Apr’01 to Mar’11 (Southern Region)

Under this mechanism, the Generators and state utilities were made accountable for the deviations from the Schedules though a component called Deviation. The Deviation rate is inversely linked to Frequency which is an indicator of surplus or deficit of Deviation

Figure 4 Illustration of Deviation concept

Indian Electricity Grid Code (IEGC) chapter 6 outlines the Scheduling procedures, revisions, priority in case of need for curtailment etc. In India, fully decentralized mechanism was adopted wherein SLDC have full autonomy to requisition as per their requirement from both the Inter State Generators as well as the intra-State ones. Length of the time block varies from 5 minutes to 60 minutes from country to Country. In India an interval length of 15 minutes was adopted for the time block for Scheduling process. Scheduling is done on a dayahead basis. It involves the GoI allocations from the Inter State Generating Stations (ISGS), Long Term Access (LTA), Medium Term Open Access (MTOA), and Short Term Open Access (STOA) transactions. They can be revised (except for STOA) during the day of operation. Every morning at 08:00 hrs, the Inter-State Generator has to declare to the RLDC its availability for every 15-min time block of the next day. The RLDC applies the Share allocation percentages given by the Ministry of Power and publishes by 10:00 AM (in its web-based program) the Entitlement of the States. By 15:00hrs, the SLDCs furnish their requisitions after considering their internal Generation vis-à-vis their expected load patterns. By about 16:30hrs, the Power Exchanges furnish their Schedules for Collective transactions. By 18:00hrs, the RLDC aggregates all the requisitions, and issues Generation Schedules to the Generators, and Drawl Schedules to the States with a notice. The Generators are free to revise the Generation capabilities depending upon the fuel quality, unit outages etc from 4th time block. The States are free to revise their Requisitions (except from Nuclear stations) during the day of operations, due to change in load patterns etc from 4th time block.

Scheduling Matrix Declared Capability of the ith Generator =[DCi] ------ Form A [Entitlement of the jth State from the ith Generator] =[DCi] x [Share ij]

------ Form B

[Requisition ij] 200 W/sq m at 50m height Wind Passes

Palghat Pass - Districts of Coimbatore, Erode Shenkottah Pass - Tirunelveli District & Tuticorin Aralvoimozhi Pass - Kanyakumari District Kambam Pass - Dindigul District

Topographical advantage

Tamil Nadu has an advantage of location, where in both the Southwest Monsoon and Northeast monsoon 'tunnel' through the Palk Bay and Gulf of Mannar, contributing to a high wind speed potential zone.

Windy Districts with recorded installations

Tirunelveli, Thoothukudi, Coimbatore, Theni District, Tiruvallur, Ramanathapuram, Dindigul, Kanyakumari

Wind Installation Statistics (Data as of 31 Mar 2015) Cumulative installed capacity (MW)

7455.00

Govt Demonstration Projects (MW)

19.36

Private Sector Projects

7435.65

All India State Ranking

# 1st (32 % of country's total wind installed capacity)

% of Wind Installations w.r.t 31.9% all sources % of Wind Installations w.r.t 88.80% all RE (Grid connected) sources

Indian Wind Power

August - September 2015

2) For drawing reactive power more than 10% of the net energy generated-50 paise per Kvarh for the entire reactive power drawn.

YoY capacity additions (MW)

Green Statistics (Data as of 31 Mar 2015) Million tonnes of CO2 emissions 16.11 million tonnes offset by Wind powered projects in the state (p.a)

Renewable Purchase Obligation (RPO) - Non Solar

10%

Prevailing APPC charges

Rs 2.63 per unit kWh

Sharing of CDM charges

Sharing on gross basis starting from 100% to developers in the first year till the sharing becomes equal (50:50) between developer and utility in the sixth year.

Current policy reference documents

1) Comprehensive Tariff Order for wind power - TNERC order no.6/2012 dt.31.07.2012 2) TNERC SMT Order no. 8/14 dt.11.12.2014 & SMT Order no. 9/14 dt. 11.12.2014 (Tx & Wheeling Charge reg.)

Million tonnes of Coal savings 11.75 million tonnes by Wind powered projects in the state (p.a) Number of homes powered

3) TNERC/M.O. 4-3 /E/RPO dated 0402-2015 (APPC for FY 14-15)

4.6 million homes

4) Notification No.TNERC / RPO /19/ !!/ dated!. 2015 (RPO draft notification)

Wind Policy - Salient Features Feed in Tariff (Sale to EB)

Rs. 3.51 per unit flat (WEGs commissioned on/or after 01 Aug 2012)

PPA Tenure

20 years

HT Industrial Tariff (for captive)

Rs. 6.35 + 5% surcharge

HT Commercial Tariff (for captive)

Rs. 8.0 + 5% surcharge

EWA Tenure

5 Years minimum period

Self Generation Tax (for captive)

10 paise per kWh

Banking (for captive)

One financial year and surplus units will be sold to Board @ 75% of PPA rate

Transmission & Wheeling charges applicable for HT

Rs. 1161.20/MW/day - Tx Charges Rs. 0.0754 per unit kWh - Wheeling charges

System Operating Charges

Rs. 300/- per day

SS O&M charges

Rs. 1.68 Lacs/ MW/ annum

Cross Subsidy Charges

Exempted

Banking Charges

94 paise per unit kWh of banked energy

Reactive Power Charges

1) For drawing reactive power up to 10% of the net energy generated-25 paise per Kvarh.

5) TNERC notification dt. 11.12.2014 (New HT tariff for consumers) & Annex

Regulatory Agencies & State Utilities Govt Nodal Agencies

Tamil Nadu Electricity Regulatory Commission (TNERC) Tamil Nadu Energy Development Agency (TEDA)

State Utilities

Tamil Nadu Electricity Board (Holding Company) Tamil Nadu Transmission Corporation Ltd (TANTRANSCO) Tamil Nadu Generation and Distribution Corporation Ltd (TANGEDCO)

Miscellaneous Factoids

August - September 2015

Indian Wind Power

Project Commencement Year

The first Wind Power Project from the Private sector was set up by M/s Pandian Chemicals. This 0.500 MW project comprised of two machines of 250 KW rating (NEPC MICON make) and was commissioned at Kattadimalai (T.N.), near Kanyakumari on 28 March 1990.

35

Snippets on Wind Power  Wind Power Shifted to White Category by CPCB Draft Document

Central Pollution Control Board (MOEF) had issued a draft document dated 19.08.2015 on revised concept of categorization of industrial sector including wind power for the comments by 04.09.15. In this draft CPCB has considered shifting of wind power from Green to White category. This was demanded by IWTMA since long.

contributions.

 India's Clean Energy Targets Way Ahead of Others: UN Official United Nations Under Secretary General and CEO for 'SE4ALL' initiative, Kandeh K Yumkella, said that India can lead the world in the area of sustainable energy from renewable sources, as its clean energy target is way ahead of the UN global goal. We believe that India can lead the world. Your (India's) targets here and some of the progress you are making here is way ahead of UN global targets. But of course, there is a lot more work to do.

On 1/8/2015 APERC has issued Tariff regulation as well as tariff order for wind.

UN's initiative SE4ALL aims that by 2030, entire world and every citizen of the world should have affordable energy access. All countries in the world should feel energy secure (by 2030) while at the same time ensuring that our consciousness to cleaner energy to climate change is also taken care of.

Tariff: Rs. 4.83 (non - AD customers) + MAT / Tax pass through Rs. 4.25 (AD customers) + MAT / Tax pass through

 Mytrah Energy’s Ravi Kailas wins Wind Power Person of

 APERC Issues Wind Tariff Order

 Ministry Moots National Renewable Energy Fund The proposed Renewable Energy Act has mooted the idea of creating a National Renewable Energy Fund (NREF with a corpus of over Rs. 17,000 crore) to support the development of renewable energy in India. A certain percentage of the National Clean Energy Fund should come annually to the proposed NREF. “State Governments may also establish a State Green Fund for the promotion of renewables. The Ministry of New and Renewable Energy “may offer a starting corpus” to such State Green Fund(s) from the National Renewable Energy Fund,” says the draft.

 Denmark Produces Country's 140% Electricity Using Wind

the year 2015 Award Mr. Ravi Kailas, Chairman and CEO, Mytrah Energy, was named the ‘Wind Power Person of the year 2015’ at the 3rd World Renewable Energy Conference in New Delhi on 23rd July 2015. Mytrah is one of the pioneers in the Indian renewable IPP industry with an operational portfolio of 543 MW within four years.

 SoftBank Keen to Invest in AP's Solar & Wind Projects Japan's telecommunications and Internet giant SoftBank Corp is interested in collaborating with the Andhra government in the renewable energy sector.

 Maharashtra Government to Allow Repowering of Wind

Power

Farms

On July 9, 2015, wind farms in Denmark produced 140% of the country’s power needs recording a surplus of 16% during the day, which swelled to 140% overnight. The Denmark government has provided a sound and crucial financial backing to the installation and development of wind farms in the country. The Denmark is likely to produce half of its energy needs through wind power before the year 2020.

In our new grid-connected renewable energy policy, the state government is planning to allow these project developers to upgrade their technologies, to ensure better capacity utilisation of wind energy projects and help them generate power at higher efficiency has allowed the re-powering of existing windmills to increase the efficiency, which was just 20-22% now.

 Government Approves Intra-State Transmission Systems for RE Cabinet Committee on Economic Affairs, Government of India has

approved the construction of intra-state transmission systems at an estimated cost of Rs. 85.5 billion running across seven states Andhra Pradesh, Gujarat, Himachal Pradesh, Karnataka, Madhya Pradesh, Maharashtra and Rajasthan. Creation of an intra-state transmission system will facilitate evacuation of renewable power from generation stations to load centres. The work is to be completed over the next three to five years involving 48 new grid sub-stations with total transformation capacity of around 17,100 MVA. Of the total cost about 40% (Rs. 34.2 billion) will be shared by the Government of India from

36

National Clean Energy Fund (NCEF), another 40% of the cost will be met by KfW loan and the rest of the 20% will be the state

Many of these wind energy projects were around 10-15 years old and hence, were using outdated technologies. Re-powering can help set up more efficient windmills and turbines, while also bringing down energy costs for consumers. This may also increase the CUF to 30-35% for higher wind zones, depending on the wind density and height of the project. The state will facilitate re-powering of installed projects and installation of new capacity.

 Solar Energy Corporation of India (SECI) to be renamed The Centre has decided to rename SECI as Renewable Energy Corporation of India (RECI) and its activities will embrace all branches of renewable energy, not solar alone. Source: Business Line

Indian Wind Power

August - September 2015

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 Policy Clarity on Wind Energy Sought

 Suzlon installs its 10,000th Wind Turbine Generator

India has the potential to achieve 60 GW of installed wind energy capacity by 2022 provided concerns related to infrastructure and grid are addressed, according to the industry. Mr. Madhusudan Khemka, Chairman of the Indian Wind Turbine Manufacturers’ Association, and Mr. D. V. Giri, its Secretary-General, told presspersons that the country aimed to scale up the installed wind energy capacity to 60 GW from the existing 23 GW in seven years. The manufacturers were going to launch the next level of machines that could be installed in low wind sites, they said. The industry was ready with 2.5 MW and 3 MW machines, and also working towards introducing storage solutions, they pointed out. However, the industry faced State-level challenges. Hence, it needed a blue print, a road map to reach the target, they said. There should be clarity on the policies by the States on wind energy.

Suzlon Group has announced installing its 10,000th WTG (wind turbine generator) during the first half of 2015. Suzlon Group, with over two decades of operating history, has cumulative installations of over 14 GW of wind energy capacity with operations across over 17 countries and customer base of more than 1700.

 India in Talks with ADB, World Bank for $2 bn Loan for PGCIL The Indian government is in talks with the World Bank and the Asian Development Bank (ADB) for providing a loan of around $2 billion to Power Grid Corporation of India Ltd. (PGCIL) to boost India’s green energy efforts by setting up transmission corridors for evacuating solar and wind power. India plans to add 175,000

 Cabinet Approves Off-shore Wind Power Generation

MW of RE capacity by 2022.

Policy Approval paves the way for offshore wind power projects up to seaward distance of 200 nautical miles. Estimates with the ministry show a potential of 106000 MW of power generation from off-shore wind installations just from the coastal regions of Gujarat. For Tamil Nadu, the estimates for power generation potential from off-shore wind energy stands at 60000 MW.

 MERC Extends RE Tariff Order MERC has extended the applicability of the existing Generic Tariff Order dated 7 July, 2014 for RE technologies till 31 October, 2015 or issue of new RE Tariff Order whichever is earlier.

 KERC Draft (Procurement of Energy from Renewable Sources) (Third Amendment) Regulations, 2015. KERC has proposed amendments to RPO targets and also specified targets for captive consumers. Targets are mentioned in the table below. Obligated Entities Distribution Licensees

RPO Non Solar Prevailing

2015-16 2016-17 2017-18 2018-19

2019-20 and onwards

BESCOM

10%

10%

12%

13%

14%

15%

MESCOM

10%

10%

14.50%

15%

15.50%

16%

CESC

10%

10%

12%

13%

14%

15%

HESCOM

7%

7%

7.50%

8.50%

9.50%

11%

GESCOM

7%

7%

5.50%

6%

7%

8%

HRECS

7%

7%

7.50%

8.50%

9.50%

11%

Deemed Licensees

0%

0%

5.50%

6%

7%

8%

Grid Connected Captive [Total capacity exceeding 5MW]

5%

5%

5.50%

6%

6.50%

7%

Any person having contracted demand 5MW with DISCOM & procuring electricity exceeding 1 MW through OA

5%

5%

5.50%

6%

6.50%

7%

Snippets Compiled by: Shri Abhijit Kulkarni General Manager, SKF India Ltd. Pune and IWTMA Team

38

Indian Wind Power

August - September 2015

Photo Feature Tamil Nadu Global Investors Meet (GIM) In an effort to build on the attractive growth prospects in Tamil Nadu, a Global Investors’ Meet was organized on 9th and 10th September, 2015, at Chennai Trade Centre, Chennai by Tamil Nadu Government. The event focused on the State’s vision of inclusive growth through investment inflows, growth in employment, balanced regional development and environmentally sustainable long term development. Tamil Nadu Energy Development Agency had a Renewable Energy Pavilion at the exhibition conducted during the meet. IWTMA had put up a stall at the meet to facilitate distribution of pamphlets of various members and also distributed Indian Wind Power magazine, tea coasters, badges at the exhibition besides projecting the IWTMA short movie.

IWTMA Chairman Sri Madhusudan Khemka at the Tamil Nadu Global Investors Meet Session on "Renewable Energy Potential and Investment Opportunities in Tamil Nadu"

Visitors at IWTMA Stall at the Global Investors Meet

Meeting regarding Special Additional Duty (SAD) A meeting of IWTMA members was conducted at Chennai on 7th September 2015 to prepare a list of additional items to be included in SAD exemption list. This list is to be submitted to MNRE.

SAD meeting in progress at Chennai on 7th September 2015

August - September 2015

Indian Wind Power

39

Know Your Member

Mr. Bharathy K CEO – Windar Renewable Energy Pvt. Ltd.

Introduction Wind turbine steel tubular tower global leader - “Windar Renewable” was founded for Asian market in Year 2012 as part of Spain’s Daniel Alonso Group at Halol, Gujarat, India. Windar is the global leader in supplying both on-shore and off-shore steel tubular towers to wind turbine manufacturers. Other business area includes manufacturing of thermal solar structures to solar industries. Being wholly owned Spanish subsidiary and India’s first 100% multinational tower manufacturing company, Windar India is backed by Spanish expertise to deliver high end tower technologies and aims to achieve the status of the only preferred top tower supplier to all leading WTG

Business Overview Windar has unique facility of Gantry Cranes in the storage yard to handle and pick any tower sections at any time or seasons. Various customer commitments indicates that the company’s intention of not just using this unit for serving the domestic market but caters to a large number of global clients. Windar Renewable has been certified by LRQA for the Quality Management System ISO 9001, the Environmental System ISO 14001 & the Occupational Health & Safety Management System ISO 18001. Windar Renewable also certified by TUV Nord Systems GmbH & Co. KG for the welding workshop in the product range of Steel Tower for Wind Turbines of the Standard DIN EN ISO 3834-2 (EN 729-2). Windar India has already supplied its towers to about 10 leading wind turbines manufacturers in India apart from Export to Brazil. Key features of Windar Renewable's Manufacturing unit at Halol Location: Halol, Vadodara, Gujarat

companies. Windar India has world class tower manufacturing facilities with many SPMs at Halol, built on an area of 15,000 sqm and has capacity to manufacture around 500 tower sets of 2 MW towers per annum.

Exclusively established for Wind Turbine Towers Area: 150,000 square meters – Workshop with three bays across an area of 15,500 square meters; office space of 1,500 square meters; and storage yard with an area of 75,000 square meters. Capacity: 10 Towers/ Week Tower Features: 2 MW, 2.1 MW-rated turbines; Sections of 6 meter diameter Windar Renewable has been contributing significantly to the group’s total revenues. The share is likely to increase with the revival of the global wind power market and favorable environment for wind power industry by Indian Government.

Management Windar India Halol Plant Besides, the factory has large areas for storage, which provides added value in terms of logistics. Windar has set up a storage yard of 75,000 square meters, which is capable of storing about 300 sections.

Mr. Bharathy – CEO, is leading the company to make Windar India a Global Hub for Towers. He is a Mechanical Engineer with specialization in Industrial Engineering and did his Master of Science by Research in Hydro Turbo Machines at IIT, Madras and having around 30 years of experience in developing and serving through all functions in 6 leading multinational companies in India. He is a certified ISO 9000 and ISO 14000 auditor and possesses good knowledge in EFQM Business Excellence models in his career and has implemented it successfully.

The Way Forward Despite several challenges in terms of raw material supply and finished goods dispatches, the company has focused its strengths in Indian wind power industry, which Mr. Bharathy believes is poised for significant growth in the coming years. Having the strong financials and technical expertise of the parent company - in manufacturing metal structures and knowledge hub for renewable energy technologies, Windar India will be offering global solutions to its clients.

Tower Manufacturing at the Plant

Considering the expertise in tower manufacturing technology and high indexes in the quality of the finishing of works and opportunities offered by the Indian wind power segment, Windar Renewable expects to emerge as the largest wind tower manufacturer in India.

Printed by R.R. Bharath and published by Dr. Rishi Muni Dwivedi on behalf of Indian Wind Turbine Manufacturers Association and printed at Ace Data Prinexcel Private Limited, 3/304 F, (SF No. 676/4B), Kulathur Road, Off NH 47 Bye Pass Road, Neelambur, Coimbatore 641062 and published at Indian Wind Turbine Manufacturers Association, Fourth Floor, Samson Towers, No. 403 L, Pantheon Road, Egmore, Chennai 600 008.

Editor: Dr. Rishi Muni Dwivedi

40

Indian Wind Power

August - September 2015

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Samson Tower, 403L, Pantheon Road, Egmore, Chennai – 600 008. Tel: +91 44 3023 0200, Fax: +91 44 30230298/99. Email: [email protected] www.regenpowertech.com Chennai: +91 98401 61228, Delhi: +91 98112 27535, Mumbai: +91 98190 63836 Factories : Andra Pradesh: Survey No.182 to 188, APIIC Industrial Park, Mambattu Village, Tada Mandal, Nellore District 524121, A.P. Udaipur: NH-76 Udaipur – Chittorgarh Road, Village – Bhatewar, Tehsil – Vallabh Nagar, Dist.Udaipur (Rajasthan), Pincode: 313601, Opp. Sir Padampath Singhnia University. An ISO 9001, ISO 114001 & OSHAS 18001 Certified Company

August - September 2015 Date of Publishing : 22.09.2015

ACE DATA, Coimbatore

Registered with REGISTRAR OF NEWSPAPERS for India, New Delhi Vide No. TNENG/2015/60605